# Separate contiguous US, Alaska, Hawaii for insets
contig = gdf[~gdf['FIPS'].isin(['02', '15'])] # exclude Alaska (02) and Hawaii (15)
alaska = gdf[gdf['FIPS'] == '02']
hawaii = gdf[gdf['FIPS'] == '15']
# Create figure
fig = plt.figure(figsize=(16, 42)) # taller figure
# -----------------------------
# 1️⃣ Death Rate Choropleth
# -----------------------------
ax_main = fig.add_axes([0.05, 0.75, 0.9, 0.22])
norm = colors.TwoSlopeNorm(vmin=gdf['death_rate'].min(),
vcenter=0,
vmax=gdf['death_rate'].max())
plot = contig.plot(
column='death_rate',
cmap='bwr_r',
linewidth=0.8,
edgecolor='black',
legend=True,
legend_kwds={'label': "Cold Mortality Rate - Heat Mortality Rate (per 100k)"},
ax=ax_main,
norm=norm
)
ax_main.axis('off')
# Move the colorbar manually
cbar = plot.get_figure().axes[-1] # the colorbar is usually the last axes
cbar.set_position([0.81, 0.715, 0.03, 0.24]) # [left, bottom, width, height] in figure coords
# Move the title above the rectangle
fig.text(
0.1, 0.965,
"Difference between Cold and Heat Related Mortality Rate by State (1999-2020)",
fontsize=16,
fontweight='bold',
ha='left'
)
ax_main.axis('off')
# Alaska inset
ax_ak = fig.add_axes([0.05, 0.69, 0.2, 0.12])
alaska.plot(column='death_rate', cmap='bwr_r', linewidth=0.8, edgecolor='black', ax=ax_ak, norm=norm)
ax_ak.axis('off')
# Label at the bottom
ax_ak.text(
0.5, -0.05, "Alaska",
ha='center', va='top', fontsize=10, transform=ax_ak.transAxes
)
# Hawaii inset (moved slightly up)
ax_hi = fig.add_axes([0.28, 0.725, 0.06, 0.04])
hawaii.plot(column='death_rate', cmap='bwr_r', linewidth=0.8, edgecolor='black', ax=ax_hi, norm=norm)
ax_hi.axis('off')
# Label at the bottom
ax_hi.text(
0.5, -0.1, "Hawaii",
ha='center', va='top', fontsize=10, transform=ax_hi.transAxes
)
# Rectangle around both insets, aligned with main map rectangle
rect_insets = patches.Rectangle(
(0.04, 0.715), # lower-left corner slightly above bottom of main rectangle
0.34, # width to cover both Alaska + Hawaii
0.065, # height to fit insets nicely
linewidth=2,
edgecolor='black',
facecolor='none',
transform=fig.transFigure
)
fig.patches.append(rect_insets)
# Main rectangle around map + insets (unchanged)
rect = patches.FancyBboxPatch(
(0.04, 0.715), # lower-left corner
0.74, # width
0.24, # height
boxstyle="square,pad=0",
fill=False,
linewidth=2,
edgecolor='black',
transform=fig.transFigure
)
fig.patches.append(rect)
# North arrow
ax_main.annotate(
'N',
xy=(0.97, 0.98), # tip of the arrow
xytext=(0.97, 0.88), # tail of the arrow
arrowprops=dict(facecolor='black', width=3, headwidth=12),
ha='center',
va='center',
fontsize=12,
xycoords='axes fraction'
)
# Add text inside the rectangle
info_text = (
"CRS:EPSG:5070\n"
"Sources: NOAA, CDC Wonder\n"
"Cartographers: Tim Van Driel and Ted Toporkov\n"
"Date: 10/13/2025"
)
rect_info = patches.Rectangle(
(0.54, 0.715), # slightly above bottom of figure
0.24,
0.02,
linewidth=1.5,
edgecolor='black',
facecolor='white',
transform=fig.transFigure
)
fig.patches.append(rect_info)
fig.text(
0.55, 0.717, # slightly inside rectangle
info_text,
fontsize=10,
va='bottom',
ha='left'
)
# -----------------------------
# 2️⃣ Cold vs Hot Deaths by State
# -----------------------------
ax2 = fig.add_axes([0.05, 0.50, 0.9, 0.14])
gdf_sorted = gdf.sort_values('cold_rate', ascending=False)
states = gdf_sorted['STATE']
x = np.arange(len(states))
width = 0.4
ax2.bar(x - width/2, gdf_sorted['cold_rate'], width, label='Cold Mortality Rate', color='blue')
ax2.bar(x + width/2, gdf_sorted['heat_rate'], width, label='Heat Mortality Rate', color='red')
ax2.set_xticks(x)
ax2.set_xticklabels(states, rotation=90)
ax2.set_ylabel("Mortality Rate")
ax2.set_title("Cold vs Heat Mortality Rates by State (1999-2020)")
ax2.legend()
# -----------------------------
# 3️⃣ Cold vs Hot Days by State
# -----------------------------
ax3 = fig.add_axes([0.05, 0.32, 0.9, 0.14])
ax3.bar(x - width/2, gdf_sorted['cold_days'], width, label='Days below 0°C', color='blue')
ax3.bar(x + width/2, gdf_sorted['hot_days'], width, label='Days above 32°C', color='red')
ax3.set_xticks(x)
ax3.set_xticklabels(states, rotation=90)
ax3.set_ylabel("Number of Days")
ax3.set_title("Cold vs Hot Days by State (1999-2020(")
ax3.legend()
# -----------------------------
# 4️⃣ Poverty Percent vs Cold Death Rate
# -----------------------------
ax4 = fig.add_axes([0.05, 0.16, 0.9, 0.12])
sns.regplot(
x='Poverty_pe',
y='cold_rate',
data=gdf,
ax=ax4,
scatter_kws={'s':50, 'color':'blue'},
line_kws={'color':'red'}
)
ax4.set_title("Poverty Percent vs Cold Death Rate (1999-2020)")
ax4.set_ylabel("Cold Death Rate (per 100k)")
ax4.set_xlabel("Poverty Percent (%)")
corr_cold = gdf['cold_rate'].corr(gdf['Poverty_pe'])
ax4.text(0.05, 0.9, f'r = {corr_cold:.3f}', transform=ax4.transAxes,
fontsize=12, bbox=dict(facecolor='white', alpha=0.5))
# -----------------------------
# 5️⃣ Poverty Percent vs Heat Death Rate
# -----------------------------
ax5 = fig.add_axes([0.05, 0.02, 0.9, 0.12])
sns.regplot(
x='Poverty_pe',
y='heat_rate',
data=gdf,
ax=ax5,
scatter_kws={'s':50, 'color':'red'},
line_kws={'color':'red'}
)
ax5.set_title("Poverty Percent vs Heat Death Rate (1999-2020)")
ax5.set_xlabel("Poverty Percent (%)")
ax5.set_ylabel("Heat Death Rate (per 100k)")
corr_heat = gdf['heat_rate'].corr(gdf['Poverty_pe'])
ax5.text(0.05, 0.9, f'r = {corr_heat:.3f}', transform=ax5.transAxes,
fontsize=12, bbox=dict(facecolor='white', alpha=0.5))
plt.show()
